Identifying and Understanding Superior Multiple-Target Visual Search Abilities

Abstract

The primary objective of this ARO-funded project was to explore a particularly troublesome issue for visual searchÑmultiple-target visual searches (where more than one target can possibly be present at the same time). Multiple-target searches are common in many settings (e.g., baggage screening, military searches), and they are especially error prone. To better understand the nature of multiple-target search to inform both academic theory and real-world performance, we enacting a multifaceted experimental approach. First, we administered laboratorybased experiments in conjunction with a large set of individual differences measures. The experiments were designed to reveal the underlying mechanisms that lead to multiple-target search errors and to reveal why some individuals are more capable searchers than others. Second, we made use of mobile app technology to examine the nature of multiple-target search from a Òbig dataÓ perspectiveÑwith billions of trials, we had the power to ask critically important nuanced questions that cannot be addressed in a laboratory setting. We made headway on both fronts, and details are provided in this report. Note that this award was ended early as the PI moved changed universities. A new award has begun that continues the efforts and more.

Document Details

Document Type
DoD Grant Award
Publication Date
Jun 25, 2021
Source ID
W911NF1410361

Entities

People

  • Stephen R. Mitroff

Organizations

  • Army Contracting Command
  • Duke University
  • United States Army

Tags

Fields of Study

  • Computer science

Readers

  • Research Science/Academic Research
  • Sensor Fusion and Tracking Systems.
  • Theoretical Analysis.